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Tests for Group-Specific Heterogeneity in High-Dimensional Factor Models

Antoine Djogbenou, Razvan Sufana

arXiv 19 Sep 2021 · Econometrics · publishedJournal of Multivariate Analysis (2023)

arXiv:2109.09049 · PDF · DOI · OpenAlex · Extracted main text

Abstract

Standard high-dimensional factor models assume that the comovements in a large set of variables could be modeled using a small number of latent factors that affect all variables. In many relevant applications in economics and finance, heterogenous comovements specific to some known groups of variables naturally arise, and reflect distinct cyclical movements within those groups. This paper develops two new statistical tests that can be used to investigate whether there is evidence supporting group-specific heterogeneity in the data. The first test statistic is designed for the alternative hypothesis of group-specific heterogeneity appearing in at least one pair of groups; the second is for the alternative of group-specific heterogeneity appearing in all pairs of groups. We show that the second moment of factor loadings changes across groups when heterogeneity is present, and use this feature to establish the theoretical validity of the tests. We also propose and prove the validity of a permutation approach for approximating the asymptotic distributions of the two test statistics. The simulations and the empirical financial application indicate that the proposed tests are useful for detecting group-specific heterogeneity.

Citation extraction

21
references
36
in-text mentions
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distinct cited
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10,450
main-text words

appendix boundary found by appendix_titled_section at “Appendix: Proofs of Results in \Cref{asym_results,perm_results} \label{appendix}” · 53% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Djogbenou, A. A (2020) Comovements in the Real Activity of Developed and Emerging Economies: A Test of Global versus Specific International Factors self0.7375260%
2Bai, J (2003) Inferential theory for factor models of large dimensions0.73732100%
3Bai, J. and S. Ng (2002) Determining the number of factors in approximate factor models0.64422100%
4Canay, I. A., J. P. Romano, and A. M. Shaikh (2017) Randomization Tests Under an Approximate Symmetry Assumption0.64422100%
5Hemerik, J. and J. Goeman (2018) Exact testing with random permutations0.64422100%
6Lehmann, E. L. and J. P. Romano (2005) Testing statistical hypotheses0.64422100%
7Chung, E. and J. P. Romano (2013) Exact and asymptotically robust permutation tests0.5112250%
8Stock, J. and M. Watson (2002) Forecasting using principal components from a large number of predictors0.51121100%
9Ando, T. and J. Bai (2017) Clustering Huge Number of Financial Time Series: A Panel Data Approach With High-Dimensional Predictors and Factor Structures0.40511100%
10Bai, J. and S. Ng (2006) Confidence intervals for diffusion index forecasts and inference for factor-augmented regressions0.40511100%

Showing the top 10 of 21 scored citations.